Method and apparatus of analyzing customer call data and related call information to determine call characteristics

ABSTRACT

A method and apparatus of processing a customer call is disclosed. The customer call may be initiated for an IVR type system or a live agent. An example method of processing the call may include receiving customer call data and recording the customer call data in a database server. The method may also include performing speech analytics on the recorded customer call data to determine instances of predefined information that occurred during the customer call, and displaying the results of the speech analytics on a user interface. The call analytics may populate a dashboard interface that provides a data analyst with an opportunity to understand the positive and negative portions of the call for future call improvement.

TECHNICAL FIELD OF THE INVENTION

This invention relates to a method and apparatus of analyzing a recordedcustomer call and/or a customer survey. More particularly, thisinvention relates to a method, apparatus, and computer program productthat permits customer call information and customer survey informationto be collected, stored and analyzed to determine customer satisfactionand other characteristics of the customer call.

BACKGROUND OF THE INVENTION

Quantitative customer survey results and other forms of customerfeedback may provide insight into a customer's level of satisfactionwith a particular company's services. Especially in instances where acustomer contacts a service department over the phone and receivescustomer support. However, receiving feedback service scores from acustomer as quantized levels of satisfaction (1—less satisfied, 2, 3, 4and 5—highly satisfied, etc.) leaves a large level of uncertainty as towhat each customer really likes or dislikes about a particular company,product and/or service.

Today, analyzing the data associated with a customer call is mostly amanual procedure. This can be burdensome and difficult to analyze as therecorded components of a customer call and how the customer rankedvarious services via a survey score are not easy to review andunderstand in a reasonable period of time. Data analysts are required toreview the survey data and identify the individual customer and theirrespective account. Next, the data analyst must also access data inremote locations to listen to the recorded call (if available) toidentify the trouble areas of the call. Once the call and/orcomment-based recordings are made available, most analysis is donemanually, on an ad-hoc level. Even advanced audio mining does notprovide a concise and real-time analysis of the customer's true customerservice experience.

If data analysis is performed without a corresponding audio miningapplication then samplings of calls must be listened to individually.This leaves different data analysts with the responsibility of makingstatements and decisions about the entire population of customers basedon various call recordings. Such a task is usually the only situationfor survey comment analysis. Any data analysis must be performed using aseparate tool and linked back manually to the macro-level customersurvey data, if linked back at all, in an effort to be efficient. Insuch instances where speech analytics are used, the entire process isperformed in disparate systems, which is long and burdensome and farfrom a real-time analysis.

SUMMARY OF THE INVENTION

One example embodiment of the present invention may include a method ofprocessing a customer call. The method may include receiving customercall data, and recording the customer call data in a database server.The method may also include performing speech analytics on the recordedcustomer call data to determine instances of predefined information thatoccurred during the customer call, and displaying the results of thespeech analytics on a user interface.

Another example embodiment of the present invention may include anapparatus configured to process a customer call. The apparatus mayinclude a receiver configured to receive customer call data, a memoryconfigured to record the customer call data, and a processor configuredto perform speech analytics on the recorded customer call data todetermine instances of predefined information that occurred during thecustomer call. The apparatus may also include a user interfaceconfigured to display the results of the speech analytics.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example logic/flow diagram of the customer'sinteraction with the call processing operations according to exampleembodiments of the present invention.

FIG. 2 illustrates an example logic/flow diagram of the query setupoperations according to example embodiments of the present invention.

FIG. 3 illustrates example screenshots of the call data that has beenprocessed and populated in a dashboard interface according to exampleembodiments of the present invention.

FIG. 4 illustrates an example flow diagram of the customer's interactionwith the call processing operations according to example embodiments ofthe present invention.

FIGS. 5A, 5B and 6 illustrate example flow diagrams of the operations ofprocessing call data and calculating customer usability scores accordingto example embodiments of the present invention.

FIG. 7 illustrates an example network entity that may be used to embodythe operations performed by the example embodiments of the presentinvention.

FIGS. 8A and 8B illustrate example screenshots of the customer usabilityscores and related call data that has been processed and populated in adashboard interface according to example embodiments of the presentinvention.

DETAILED DESCRIPTION OF THE INVENTION

It will be readily understood that the components of the presentinvention, as generally described and illustrated in the figures herein,may be arranged and designed in a wide variety of differentconfigurations. Thus, the following detailed description of theembodiments of a method, apparatus, and system, as represented in theattached figures, is not intended to limit the scope of the invention asclaimed, but is merely representative of selected embodiments of theinvention.

The features, structures, or characteristics of the invention describedthroughout this specification may be combined in any suitable manner inone or more embodiments. For example, the usage of the phrases “exampleembodiments”, “some embodiments”, or other similar language, throughoutthis specification refers to the fact that a particular feature,structure, or characteristic described in connection with the embodimentmay be included in at least one embodiment of the present invention.Thus, appearances of the phrases “example embodiments”, “in someembodiments”, “in other embodiments”, or other similar language,throughout this specification do not necessarily all refer to the samegroup of embodiments, and the described features, structures, orcharacteristics may be combined in any suitable manner in one or moreembodiments.

In addition, while the term “message” has been used in the descriptionof embodiments of the present invention, the invention may be applied tomany types of network data, such as packet, frame, datagram, etc. Forpurposes of this invention, the term “message” also includes packet,frame, datagram, and any equivalents thereof. Furthermore, while certaintypes of messages and signaling are depicted in exemplary embodiments ofthe invention, the invention is not limited to a certain type ofmessage, and the invention is not limited to a certain type ofsignaling.

Example embodiments of the present invention may include providingdynamic and interactive access to a customer's recorded call, and accessto recorded responses available from a survey dashboard application.Such a dashboard interface may include a graphical user interface (GUI)that is customized for the data analyst's preferences. The surveyresults may be present on the dashboard interface and may be viewed by adata analyst.

The survey may provide insight into the customer's experiences. Thecustomer records may provide analysis results on individual calls and/orcomments across a pool of customers to provide insight into thecompany's customer satisfaction scores. The analysis of customer recordsmay lead to information used to deliver tangible results into what needsto be fixed to improve customer satisfaction scores and overall customersatisfaction.

FIG. 1 illustrates an example logic diagram of a service call, accordingto example embodiments of the present invention. Referring to FIG. 1, atthe time of a service call, a customer 100 contacts their serviceprovider and speaks with a live customer service agent 110B or anautomated interactive voice response (IVR) application 110A. Thecustomer call is recorded at operation 120, and upon completion of thecall the customer is offered a survey at operation 130. The results ofthe conversation and survey are written to a central repository 141 atoperation 140. The conversation data and survey data may be written inreal-time to the centralized repository 141, which may be a local orremote database server.

As noted above, at the completion of a call, a survey is provided to thecustomer to gauge their level of satisfaction with the level of serviceprovided. Survey scores may include both numeric data (i.e., thecustomer selects a numeric field ranking in response to a surveyquestion) and/or free-form text or voice files recorded for a customerverbatim comment. Survey results may be written in near real-time to thecentralized repository 141.

Once the call is written to memory, near real-time speech analyticqueries may be executed against the recorded call data and speechrecorded survey comments (if available). The analytics are based onpredefined terms and plain language responses to see if a match is foundfor any of the pre-defined queries. For example, words and phrases, suchas, “hate”, “not like”, “not”, “no”, and other negative words andphrases may be discovered from audio recordings of the customer's voice,and data file transcripts of the customer's conversation, which may becreated after the customer's voice is recorded.

In another example, positive words and phrases, such as, “like”,“satisfied”, “happy”, “pleased”, “good”, etc., may also be discoveredfrom speech analytic queries based on predefined query content. Thesepositive words and phrases may provide the customer service feedbackprocedure with info'rmation regarding the elements of the call that areapproved by the customer(s). The speech analytic queries are performedon the call data and recorded comments of the survey data at operation150. Next, a lookup of customer demographic data, customer account data,and any transactional data, is also performed and associated with boththe customer call and the customer survey, at operation 160. All ofthese portions of data are linked together within the centralizedrepository 141 to provide data metric reports, graphs and otherinformation reporting tools that may be useful for a customer or servicerepresentative viewing the results of the customer call and/or customersurvey.

The individual numeric customer survey results and other reporting datamay be displayed within the client dashboard 171 at operation 170, alongwith a link to the recorded call, and a visual legend that indicateswhich (if any) pre-defined query results were present within the call.Details of the dashboard data are illustrated in FIG. 3, and arediscussed in detail below. Other example dashboard data may include anyconfidence scores associated with the customer survey results or calldata, and key demographic data associated with the customer. This dataprovides the data analyst with a customized user interface to view,manipulate and analyze the results of the customer or customers andtheir experiences with the service offered by the IVR application orlive agent.

All macro-level statistics related to the survey scores, analytics queryresults, demographic data, etc. are updated to include the new call. Thenew calls are a constant progression for continually updating theprevious statistics and other dashboard data. A media player isdisplayed within the dashboard and provides the ability to listen to anindividual recorded call. This media player provides a flexible toolthat will allow easy navigation throughout the recorded call. The audiofiles for calls and comments may also display where in the call eachparticular query matched, visually.

FIG. 3 illustrates results of the data analytics, according to exampleembodiments of the present invention. Referring to FIG. 3, a queryoutput result 301 may include an audio file that is created during theanalytic process and placed with a simple play option in the dashboarddisplay 306. Each audio file is analyzed to determine for each query ifthere is a “hit”, yes or no, (Y/N) based on a predefined search term,and the location or time within the audio file of the hit (see dashboarddata snapshot 302). Further analysis of the audio files #1, #4, #5,etc., demonstrates that certain queries may be performed for bothcompetitor related data and product related data. The specific termsbeing analyzed will provide a hit at certain locations in the audiofiles.

As for survey data results, survey data results 303 include respondentdemographics and numeric survey responses. Referring to the dashboarddata snapshot 304, various survey data #1 through #5 are illustrated asincluding various different information segments under the customer'sdemographics to determine information about the customer. Next, thesurvey response may be illustrated for certain questions to determine ifthere are weak areas for all customer responses.

Additional data is included in dashboard data snapshot 306, which isrelated to audio files for the survey 305, and includes recorded callaudio or recorded survey audio. The audio is provided with menu optionsto listen to the tagged segments of audio corresponding to the call orsurvey comments. This provides the data analyst with an opportunity totarget the exact locations where the audio should be manually inspectedto determine the true problems associated with a particular call. Forexample, if survey #3 shows poor survey numeric response (4, 1, 1), thenthe call could be inspected to determine if the survey #3 correspondingto the particular customer is simply an angry customer with no reasonfor ranking the survey poorly, or, if something unexpected happenedduring the call which could be easily fixed. Nevertheless, the entirecall should not be screened to find such negative information.

In order to target the desired call and survey data to populate acustomized dashboard, before the process begins, the service providerworks with a business analyst to define the analytic areas they wouldlike to research within their calls. FIG. 2 illustrates the query setupand data auditing menus used to create the data queries, according toexample embodiments of the present invention. Referring to FIG. 2,examples of analysis areas may include, but are not limited tocompetitive or marketing analysis, new product or service tracking,agent issues, coaching opportunities and overall call center management,legal and script adherence, and overall call or comment types.

Client input may be provided by manual entry or a data file 201 ofspecific query content within certain categories, such as, competitornames, product names, marketing offers, positive sentiment (surveycomments only), negative sentiment (survey comments only) and agentapology (full call only). This means that any instances of predeterminedwords and phrases associated with these categories may be audited andstored in memory for future analysis.

Once the client's selected search criteria has been established, theanalytics team may implement the desktop query builder application 202to setup and execute the queries. Small samples of recordings may beproduced in any file format at operation 202A, the created queries aresetup at operation 202B and the queries are loaded into the builderapplication 202C. The data feed of survey comments and call recordingsat operation 203 are provided to the query session 204. Each queryoutput is performed and corresponding audio files are produced perquery. A “hit” indicator of yes or no (Y/N) is also provided to show ifan audio segment had any positive hits for a particular query, atoperation 205. The location of the audio file where the hit occurred istracked and stored in memory to populate the data analyst dashboard.Once the audio files are created they may be deleted or archived forfuture reference, at operation 205.

The speech analyst application creates a series of queries within thespeech analysis tool, which is designed to identify/capture anyinstances of the desired analysis data. Performing a query for certainsearch terms may require a number of queries each of which is aimed atdifferent key phrases spoken by customers that are the same, similar orrelated to the analysis target areas.

The results of the speech analytics performed on the recorded customercalls and/or recorded comments (when used) that are associated with aset of customer surveys may be displayed on the data analysts' dashboardGUI. Customer calls and/or comments are recorded at the time the call istaken. At the point in time when the call is written to the servermemory, a pre-defined set of speech analytics queries are run againstthe call. The purpose of these queries is to determine if the callcontains any spoken phrases/words that match the analysis goals set bythe clients.

Examples of queries could include, but are not limited to a companyanalyzing all calls for mentions of a competitor's name, analyzing callsfor specific mentions of a product or service, searching for calls wherea customer voices concern with the agent service, validating agentadherence with the pre-defined customer service scripts, particularlypositive or negative language being used, etc.

A client-facing dashboard 171 provides access to certain data areas, alllinked together, such as, numeric survey score data, at both theindividual caller and macro level, demographic data associated with thecaller/survey respondent, the recorded customer call linked to anindividual survey and recordings of any customer comments tied to thesurvey, and capability to play and hear these recordings on the spotusing a built-in media player.

Any and all audio mining results linked to any of these recordings mayinclude visual identification of analysis areas with a “match” for eachcustomer call (e.g. a specialized icon displayed for each call thatcontains a “match” to the pre-defined analysis areas), any confidencescoring related to the analysis areas, and data about when the recorded“match” occurred. Macro-level results for the analysis areas may also bedisplayed on the dashboard 171, illustrating the total number of callswith analysis results matching the pre-defined queries (e.g. the numberof calls when a competitor name was mentioned during the relevanttimeframe). The ability to “drill-down” from the macro-level analysisresults into the individual recorded calls, displaying the associatedsurvey data, and the ability to view trending data for allsurvey/demographic/query result data are also capabilities of thedashboard display of analytic data.

One example method according to example embodiments of the presentinvention may include a set of operations illustrated in FIG. 4.Referring to FIG. 4, a customer initiates a call to a service center andthe call is recorded, at operation 401. Next, a survey may be offered tothe customer and the results of the customer's responses are alsorecorded, at operation 402. The call is stored and the survey resultsare both stored in a server, at operation 403. Next a speech analyticquery or queries are performed on the stored call data, at operation404. The results of the speech analytics are then published and linkedto a client dashboard to permit a data analyst to review the results, atoperation 405. This display provides an overall ability to analyzewithin a single dashboard all survey/demographic/query data resultstogether.

Other example embodiments may provide ways to leverage interactive voiceresponse (IVR) application performance data to calculate a numericcustomer usability score. Usability may be calculated based on thenumber of attempts a caller requires to successfully respond to eachdialog prompt offered in an IVR call session. The number of times aspeech application needs to confirm caller input may also be part of theusability score process.

A numeric score may be assigned to the number of attempts a userrequires to successfully satisfy an IVR menu option, in turn, a score isderived from those attempts. A low score for a call indicates poorusability during that call, which is likely a call where the callerencountered a number of errors and/or poor speech recognition wascommunicated. Call data can be aggregated in a number of ways to measureapplication usability across customer segments, periods of time,geographic regions, etc. The call data may also be a valuable tool tobenchmark application performance. For example, a company may seek totrack the impact of application changes internally and externally todetermine customer usability against industry competitor applications.

Application usability by potential customers can often be subjective anddifficult to quantify. Usability of an IVR application varies fromcaller to caller and often varies significantly within different partsof the application. Poor usability can result in low customersatisfaction and increased application cost (due to longer calls).Furthermore, unsatisfied customers may quit subscription services andcompanies may suffer business loss as a result of poor customer servicesatisfaction ratings.

By assigning a numeric usability score to each IVR prompt that indicateshow easy it was for the caller to navigate through that prompt, it maybe easier to track each portion of an IVR call and fix problem areas ofthe IVR call process. A customer usability score is calculated based onthe number of attempts required at each prompt, and a point score isassigned to each successful prompt. Points are deducted for each time aspeech application must confirm a caller's response, as this indicates aless usable experience.

A usability score is calculated for each call processed by the IVRsystem, and can be aggregated many ways for reporting, analysis andbenchmarking purposes. For example, usability for a unique caller or acaller segment (by value, geography, tenure, revenue, etc.), usabilityfor a specific timeframe (daily, weekly, monthly usability score, etc.),as a measure before/after an application change (to determine impact onapplication usability), are all examples of data that may be reportedbased on usability scores.

FIG. 5A illustrates an example customer call with an IVR system.Referring to FIG. 5A, a customer calls a company and initiates an IVRmenu at operation 501. The company side of the IVR system captures theIVR input (speech, responses, errors, etc.) at operation 502. Inoperation, the caller attempts to satisfy each IVR prompt (e.g., spokeninformation, numeric information, requested information, etc.), whichare tracked and recorded. Each attempt is assigned a numeric score, suchas, for example, “1”, at operation 503. A point score is assigned toeach IVR prompt. “1” point is assigned for a successful result that endswith “success” or “command.” If a confirmation prompt is required (dueto a caller response without an adequate level of recognitionconfidence) and the caller is successful, ½ point may be assigned.

The total number of attempts and total number of points are summedtogether at the end of each call. A usability score is calculated forthe individual call at operation 504. The formula used to calculate theusability score may be {Usability Score=Total Points/Total Attempts}.The usability data for all calls for a current day or similar time framemay also be aggregated at operation 505. The usability score may also becalculated for a current day in near real-time at operation 506. Theusability score may be linked to the customer dashboard at operation507. A competitive analysis of the application usability may also beperformed to determine customer data that represents information helpfulto understand competitor offerings and services.

The output of the analysis continues with FIG. 5B at operation 509 whichdetermines whether the usability score is a good score or a poor score.If the usability is good, the daily usability monitoring at operation510 submits the results to the competitive analysis of the applicationusability of operation 508, where a competitive analysis may beperformed before ending the analysis. If the usability is poor, the dataanalyst may view the data and identify problem areas at operation 511based on the source of the poor usability score. Once a determination ismade as to the problems encountered, improvements may be recommended atoperation 512 and changes implemented at operation 513. The flow of datathen proceeds to return back to operation 501 where a recursive model isperformed to accept input from the next customer before continuing alongthe process.

Usability scores for all calls during the current day are summed andused to determine a single usability score for that day's applicationperformance using a formula, such as, {Current Day Usability Score=Sumof Usability Score for All Calls/Total Number of Calls}. The usabilityscore is displayed visually on the dashboard and is updated in real-timeas new calls are processed. The usability scores may also be aggregatedfor specific timeframes and caller segments by aggregating the usabilityscore for the unique group and dividing it by the total number of callsfor the segment/timeframe.

FIG. 6 illustrates an example logic diagram representing the operationof the caller accessing the IVR application, according to exampleembodiments of the present invention. Referring to FIG. 6, the customercontact is initiated by the caller 100 placing a call to the servicecenter IVR application 601. The customer's interaction data is recordedand evaluated to calculate an individual usability score at operation602. The application results are aggregated and a competitivebenchmarking analysis may be performed to compare the user's experiencewith competitors' features and options at operation 603. If theconclusion is that usability is poor and could be improved then arecommendation is performed to implement IVR changes at operation 604.The results are displayed on the client dashboard 606, and reports arepopulated based on the customer usability score and other customerinformation at operation 605.

The operations of a method or algorithm described in connection with theembodiments disclosed herein may be embodied directly in hardware, in acomputer program executed by a processor, or in a combination of thetwo. A computer program may be embodied on a computer readable medium,such as a non-transitory storage medium. For example, a computer programmay reside in random access memory (“RAM”), flash memory, read-onlymemory (“ROM”), erasable programmable read-only memory (“EPROM”),electrically erasable programmable read-only memory (“EEPROM”),registers, hard disk, a removable disk, a compact disk read-only memory(“CD-ROM”), or any other form of storage medium known in the art.

An exemplary storage medium may be coupled to the processor such thatthe processor may read information from, and write information to, thestorage medium. In the alternative, the storage medium may be integralto the processor. The processor and the storage medium may reside in anapplication specific integrated circuit (“ASIC”). In the alternative,the processor and the storage medium may reside as discrete components.For example FIG. 7 illustrates an example network element 700, which mayrepresent any of the above-described network components 100, 110A, 141,171.

As illustrated in FIG. 7, a memory 710 and a processor 720 may bediscrete components of the network entity 700 that are used to executean application or set of operations. The application may be coded insoftware in a computer language understood by the processor 720, andstored in a computer readable medium, such as, the memory 710.Furthermore, a software module 730 may be another discrete entity thatis part of the network entity 700, and which contains softwareinstructions that may be executed by the processor 720. In addition tothe above noted components of the network entity 700, the network entity700 may also have a transmitter and receiver pair configured to receiveand transmit communication signals (not shown).

FIGS. 8A and 8B illustrate example tables 800 that include the data fromcalculated usability scores. For example, the event 801 may include aspecific prompt experienced by a customer, such as, “what purpose areyou calling for”, “technical difficulties”, “billing concerns”, etc.That event 801 may or may not have been successful at retrieving apositive user response. The result 802, points 803 and attempts 804,represent the end result (success or failure), the number of pointsawarded and the number of attempts required, respectively. An overallpercentage of success may be calculated in column 805 as a usabilityscore. FIG. 8B illustrates a final number of points and attempts and afinal overall usability score in column 805.

While preferred embodiments of the present invention have beendescribed, it is to be understood that the embodiments described areillustrative only and the scope of the invention is to be defined solelyby the appended claims when considered with a full range of equivalentsand modifications (e.g., protocols, hardware devices, software platformsetc.) thereto.

What is claimed is:
 1. A method of processing a customer call, themethod comprising: receiving customer call data; recording the customercall data in a database server; performing speech analytics on therecorded customer call data to determine instances of predefinedinformation that occurred during the customer call using a plurality ofanalytic queries that are searching for specific words and phrases thatsatisfy content requirements of the analytic queries; analyzing thecustomer call data to create a plurality of audio recording files eachof which are created based on specific content of the analytic queries,each of which represents a portion of the call data; and displaying theresults of the speech analytics on a user interface.
 2. The method ofclaim 1, wherein the customer call data is recorded based on thecustomer's input and interaction with at least one of a live agent andan automated interactive voice response (IVR) application.
 3. The methodof claim 2, further comprising: offering the customer a survey after thecall interaction has completed; and storing the results of the customercall data and the survey in the same database server.
 4. The method ofclaim 1, wherein the analytic queries are based on at least one ofcompetitor names, product names, marketing offers, positive sentiment,negative sentiment and agent apology.
 5. The method of claim 1, furthercomprising: populating the client interface with the audio files toprovide real-time access to the portions of the call data associatedwith customer call and survey results.
 6. An apparatus configured toprocess a customer call, the apparatus comprising: a receiver configuredto receive customer call data; a memory configured to record thecustomer call data; a processor configured to perform speech analyticson the recorded customer call data to determine instances of predefinedinformation that occurred during the customer call using a plurality ofanalytic queries that search for specific words and phrases that satisfycontent requirements of the analytic queries, and the processor isfurther configured to analyze the customer call data to create aplurality of audio recording files each of which are created based onspecific content of the analytic queries, each of which represents aportion of the call data; and a user interface configured to display theresults of the speech analytics.
 7. The apparatus of claim 6, whereinthe customer call data is recorded based on the customer's input andinteraction with at least one of a live agent and an automatedinteractive voice response (IVR) application.
 8. The apparatus of claim7, wherein the processor is further configured to offer the customer asurvey after the call interaction has completed, and the memory isfurther configured to store the results of the customer call data andthe survey.
 9. The apparatus of claim 6, wherein the analytic queriesare based on at least one of competitor names, product names, marketingoffers, positive sentiment, negative sentiment and agent apology. 10.The apparatus of claim 6, wherein the processor is further configured topopulate the client interface with the audio files to provide real-timeaccess to the portions of the call data associated with customer calland survey results.
 11. A non-transitory computer readable storagemedium comprising instructions that when executed cause a processor toprocess a customer call, the processor being further instructed toperform: receiving customer call data; recording the customer call datain a database server; performing speech analytics on the recordedcustomer call data to determine instances of predefined information thatoccurred during the customer call using a plurality of analytic queriesthat are searching for specific words and phrases that satisfy contentrequirements of the analytic queries; analyzing the customer call datato create a plurality of audio recording files each of which are createdbased on specific content of the analytic queries, each of whichrepresents a portion of the call data; and displaying the results of thespeech analytics on a user interface.
 12. The non-transitory computerreadable storage medium of claim 11, wherein the customer call data isrecorded based on the customer's input and interaction with at least oneof a live agent and an automated interactive voice response (IVR)application.
 13. The non-transitory computer readable storage medium ofclaim 12, wherein the instructions further provide: offering thecustomer a survey after the call interaction has completed; and storingthe results of the customer call data and the survey in the samedatabase server.
 14. The non-transitory computer readable storage mediumof claim 11, wherein the analytic queries are based on at least one ofcompetitor names, product names, marketing offers, positive sentiment,negative sentiment and agent apology.
 15. The non-transitory computerreadable storage medium of claim 14, wherein the instructions furtherprovide: analyzing the customer call data to create a plurality of audiorecording files each of which are created based on specific content ofthe analytic queries, each of which represents a portion of the calldata.